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Boost VQEs with DBI

Boosting variational eigenstate preparation algorithms limited by training and not device coherence by diagonalization double-bracket iteration.

Installation instructions

The package can be installed by source after cloning the repository:

cd boostvqe
pip install .

Code structure

The file src/boostvqe/boost.py performs boosted VQE training.

The source code is located in ./src/boostvqe/. and its composed of:

  • ansatze.py: contains circuit used by VQE
  • utils.py: contains utils function used by main.py
  • plotscripts.py: plotting functions.
  • compiling_XXZ.py: compilation for XXZ model.

Example

It follows a python snippet explaining how to run the boosting

from boostvqe.boost import dbqa_vqe
from boostvqe.ansatze import hdw_efficient

from qibo.models.dbi.double_bracket import DoubleBracketGeneratorType

circuit = hdw_efficient(nqubits=2, nlayers=2)
output_folder = "output"
dbqa_vqe(circuit, output_folder, mode = DoubleBracketGeneratorType.group_commutator)

All the info regarding dbqa_vqe can be generated with help(dbqa_vqe).

Tutorials

Some useful notebooks to understand how the library works, are collected here.

Reference and citation

For more details about this project and citations, please refer to the article.

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Using DBI to boost VQE optimization

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